A recent consensus conference concluded that there are no diagnostic criteria specific for differentiating between systemic inflammation and sepsis, and that a lack of sepsis molecular markers underscores the challenge still present in diagnosing sepsis. In preliminary studies, we systematically tested the hypothesis that circulating leukocyte gene expression profiles and plasma proteomic profiles can be used to diagnose sepsis and model the response to systemic inflammation. Having proved our hypothesis in preclinical models, we are now ready to move to the bedside. One of the very few data-rich environments where infection can be predicted on a population basis is the intensive care unit (ICU), typically manifested as ventilator-associated pneumonia (VAP). We hypothesize that circulating leukocyte RNA and plasma protein profiles over time in patients can be used to model the host response to sepsis secondary to VAP, and that the application of this model to clinical decision making will significantly improve our diagnostic and prognostic capabilities. To test this hypothesis, we established the University-wide infrastructure necessary, involving faculty from the departments of Surgery, Anesthesiology, Medicine, Pediatrics, Genetics, Pathology and Immunology, Radiation Oncology, Biostatistics, Systems Engineering, Computer Science, and Mathematics. In Aim 1, we measure changes over time in the circulating leukocyte transcriptome and plasma proteome of patients at risk for VAP. In Aim 2, we model the host response to VAP using generic and organism-specific markers that differentiate between patients who respond or do not respond to therapy. The optimized sample collection protocols are in use. Serial blood samples are drawn over 21 days from intubated patients at risk for VAP. Pilot data from the first two patients are presented herein, describing the clinical trajectory of Gram-negative pneumonia. Funds from this award are necessary to generate the preliminary data for a larger study, to untangle the septic response from the systemic inflammatory response.